Innovation and partners shorten the path to an AI-driven industry

It was high mass again at Hannover Messe. Siemens showcased advances in industrial AI, software-defined automation and digital-twin technology. Innovations that, combined with a strong ecosystem of partners, will accelerate digital transformation and sustainability in industries towards an AI-driven future. As part of its transformation into a ONE Tech Company, Siemens is aligning its portfolio, investments and organisation to scale innovation and bring together software, automation and AI. This progress strengthens Siemens' role as a leader in industrial innovation and supports customers worldwide to become more competitive, resilient and sustainable.

“This Hannover Messe took place at an exciting time. Industries are facing drastic changes in technology and their markets. As a leader in industrial AI, extended digital twins and software-defined automation, we offer the technologies our customers need to become more resilient, competitive and sustainable,” said Roland Busch, president and CEO of Siemens AG. The biggest technological lever is industrial artificial intelligence. He sees a huge opportunity for industry: “We have domain knowledge - we understand our industries. And we have the data. Together with AI, this is a winning combination.” To illustrate this shift, Siemens showed at Hannover Messe key innovations such as new developments within Siemens Xcelerator and the expansion of Industrial Copilot.

More IT and OT integration with Microsoft

In the past, industrial companies managed data in separate IT and OT environments. Today, to make production more adaptive, OT and IT need to converge. Edge computing plays a crucial role by bridging the gap between shop floor and cloud, allowing data to be captured and processed directly at source. Siemens Industrial Edge's powerful OT data layer easily works with Azure IoT Operations to create an interoperable OT and IT data layer for manufacturing. It enables manufacturers to deploy responsive, reliable, flexible and secure applications to optimise operations, reduce costs and increase uptime and quality.

Turning shop floor data into real results

Together, Siemens and Microsoft enable industrial manufacturers to implement edge-to-cloud use cases. To improve the overall efficiency of equipment and value streams on the shop floor, data delivered by Siemens Industrial Edge to Azure IoT Operations and Azure cloud services can be used to create digital twins. The collaboration also allows live production data to be used with generative AI capabilities to improve employee skills and operations. The Siemens Industrial Copilot for Operations helps operators solve problems and access machine information through natural language queries.

AI-powered maintenance with Industrial Copilot

And that Industrial Copilot, meanwhile, is more comprehensive than you remember it from its baptism of fire at last year's Hannover Messe. And also a trophy richer: Siemens' solution was awarded the Hermes Award. Because Industrial Copilot enables customers to deploy generative AI across the entire value chain - from design and planning to engineering, operations and services. As a result, engineering teams, for example, generate code for PLCs in their own language, an estimated 60% faster, while minimising errors and requiring less specialised knowledge. This in turn reduces development time and increases quality and productivity in the long run. Siemens is developing a full suite of copilots to industry standards and is now strengthening its offering with the launch of an advanced maintenance solution designed to redefine industrial maintenance strategies towards an intelligent, data-driven approach. To achieve this, the Senseye Predictive Maintenance solution, supported by Microsoft Azure, is being extended with two new offerings:

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  Entry-level package: this solution provides an accessible and cost-effective introduction to predictive maintenance, combining AI-driven repair guidance with predictive baseline capabilities. It helps companies transition from reactive to condition-based maintenance by providing limited connectivity for sensor data collection and real-time condition monitoring. With AI-assisted troubleshooting and minimal infrastructure requirements, companies can reduce downtime, improve maintenance efficiency and lay the foundation for fully predictive maintenance.
• Scale package: designed for companies looking to completely transform their maintenance strategy, this package integrates Senseye Predictive Maintenance with full Maintenance Copilot functionality. It enables customers to predict failures before they occur, maximise uptime and reduce costs with AI-driven insights. Offering scalability across the enterprise, automated diagnostics and sustainable business outcomes, this solution helps companies go beyond traditional maintenance, optimising operations across multiple sites while supporting efficiency and resilience over the long term.